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We report an experimental demonstration of effective entanglement in a prepare&measure type of quantum key distribution protocol. Coherent polarization states and heterodyne measurement to characterize the transmitted quantum states are…

Quantum Physics · Physics 2009-11-13 S. Lorenz , J. Rigas , M. Heid , U. L. Andersen , N. Lütkenhaus , G. Leuchs

In many branches of engineering, Banach contraction mapping theorem is employed to establish the convergence of certain deterministic algorithms. Randomized versions of these algorithms have been developed that have proved useful in…

Probability · Mathematics 2023-09-25 Abhishek Gupta , Rahul Jain , Peter Glynn

We propose and theoretically study a method for the stochastic realization of arbitrary quantum channels on multimode single-photon qudits. In order for our method to be undemanding in its implementation, we restrict our analysis to…

Quantum Physics · Physics 2012-03-21 Marco Piani , David Pitkanen , Rainer Kaltenbaek , Norbert Lutkenhaus

In this work we propose a simple optical architecture, based on phase-only programmable spatial light modulators, in order to characterize general processes on photonic spatial quantum systems in a $d>2$ Hilbert space. We demonstrate the…

Quantum Physics · Physics 2023-01-27 Juan José Miguel Varga , Lorena Rebón , Quimey Pears Stefano , Claudio Iemmi

The distillable randomness of a bipartite quantum state is an information-theoretic quantity equal to the largest net rate at which shared randomness can be distilled from the state by means of local operations and classical communication.…

Quantum Physics · Physics 2023-07-06 Ludovico Lami , Bartosz Regula , Xin Wang , Mark M. Wilde

So far, there have been plenty of literatures on the metric in the space of probability distributions and quantum states. As for channels, however, only a little had been known. In this paper, we impose monotonicity by concatenation of…

Quantum Physics · Physics 2010-06-03 Keiji Matsumoto

We present experimentally and numerically accessible quantities that can be used to differentiate among various families of random entangled states. To this end, we analyze the entanglement properties of bipartite reduced states of a…

Quantum many-body systems display an extraordinary degree of complexity, yet many of their features are universal: they depend not on microscopic details, but on a few fundamental physical aspects such as symmetries. A central challenge is…

Quantum Physics · Physics 2026-02-02 Jia-Nan Yang , Lata Kh Joshi , Filiberto Ares , Yihang Han , Pengfei Zhang , Pasquale Calabrese

A random phase property establishing a link between quasi-one-dimensional random Schroedinger operators and full random matrix theory is advocated. Briefly summarized it states that the random transfer matrices placed into a normal system…

Mathematical Physics · Physics 2010-06-04 Rudolf A Roemer , Hermann Schulz-Baldes

We adopt the perspective of similarity equivalence, in gate set tomography called the gauge, to analyze various properties of quantum operations belonging to a semigroup, $\Phi= e^{{\cal L}t}$,and therefore given through the Lindblad…

Quantum Physics · Physics 2019-06-26 Zbigniew Puchała , Łukasz Rudnicki , Karol Życzkowski

We prove that the local eigenvalue statistics for $d=1$ random band matrices with fixed bandwidth and, for example, Gaussian entries, is given by a Poisson point process and we identify the intensity of the process. The proof relies on an…

Mathematical Physics · Physics 2020-09-01 Benjamin Brodie , Peter D. Hislop

We study the possibility of performing quantum state reconstruction from a measurement record that is obtained as a sequence of expectation values of a Hermitian operator evolving under repeated application of a single random unitary map,…

Quantum Physics · Physics 2010-04-29 Seth T. Merkel , Carlos A. Riofrio , Steven T. Flammia , Ivan H. Deutsch

In order to understand the resourcefulness of a natural quantum system in quantum communication tasks, we study the dense coding capacity (DCC) and teleportation fidelity (TF) of Haar uniformly generated random multipartite states of…

Quantum Physics · Physics 2021-03-24 Rivu Gupta , Shashank Gupta , Shiladitya Mal , Aditi Sen De

A fundamental task in quantum information is to approximate a pure quantum state in terms of sparse states or, for a bipartite system, states of bounded Schmidt rank. The optimal deterministic approximation in each case is straightforward,…

Quantum Physics · Physics 2026-01-06 Aram W. Harrow , Angus Lowe , Freek Witteveen

With the recent claim of a quantum advantage demonstration in photonics by Zhong et al, the question of the computation of lower-order approximations of boson sampling with arbitrary quantum states at arbitrary distinguishability has come…

Quantum Physics · Physics 2021-01-01 Jelmer J. Renema

In the quantum state tomography problem, one wishes to estimate an unknown $d$-dimensional mixed quantum state $\rho$, given few copies. We show that $O(d/\epsilon)$ copies suffice to obtain an estimate $\hat{\rho}$ that satisfies…

Quantum Physics · Physics 2015-09-15 Ryan O'Donnell , John Wright

We analyze general enough models of repeated indirect measurements in which a quantum system interacts repeatedly with randomly chosen probes on which Von Neumann direct measurements are performed. We prove, under suitable hypotheses, that…

Mathematical Physics · Physics 2015-06-05 Michel Bauer , Tristan Benoist , Denis Bernard

The problem of an optimal mapping between Hilbert spaces $IN$ and $OUT$, based on a series of density matrix mapping measurements $\rho^{(l)} \to \varrho^{(l)}$, $l=1\dots M$, is formulated as an optimization problem maximizing the total…

We investigate the spectral statistics of the difference of two density matrices, each of which is independently obtained by partially tracing a random bipartite pure quantum state. We first show how a closed-form expression for the exact…

Mathematical Physics · Physics 2016-12-12 José Mejía , Camilo Zapata , Alonso Botero

Clustering is an important exploratory data analysis technique to group objects based on their similarity. The widely used $K$-means clustering method relies on some notion of distance to partition data into a fewer number of groups. In the…

Machine Learning · Statistics 2022-10-14 Yubo Zhuang , Xiaohui Chen , Yun Yang